Software Quality Assurance

en Limba Engleză Hardback – 8 feb 2018

This book introduces Software Quality Assurance (SQA) and provides an overview of standards used to implement SQA. It defines ways to assess the effectiveness of how one approaches software quality across key industry sectors such as telecommunications, transport, defense, and aerospace.

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Specificații

ISBN-13: 9781118501825
ISBN-10: 1118501829
Pagini: 624
Dimensiuni: 152 x 229 x 34 mm
Greutate: 1.04 kg
Ediția:Revised.
Editura: Wiley
Locul publicării:Hoboken, United States

Public țintă

Primary audience: Upper–level software engineering students
Secondary audience: Practicing software engineers

Cuprins

Notă biografică

Claude Y. Laporte, PhD, has coordinated the development, implementation, and deployment of systems and software engineering processes and project management processes, and has trained software engineers in America, Europe, and Asia. Since 2000, he has been a professor at the École de technologie supérieure (ÉTS), a Canadian engineering school, where he teaches software engineering. In 2013, Professor Laporte was awarded an honorary doctorate for his contributions to software engineering. He is the Project Editor of the set of ISO/IEC 29110 systems and software engineering life cycle standards and guides developed specifically for Very Small Entities (VSEs). He has also written two French software engineering textbooks with Dr. April. Dr. Laporte is a co-author of another book targeted at managers of small systems engineering organizations. Alain April, PhD, is a full professor of software engineering and IT at ÉTS University, Québec, Canada. He specializes in software quality assurance and IT process mapping/conformity in the industry transfer of Big Data HPC applications based on Spark, H2O.ai, and other cloud computing technologies applied to healthcare, construction, banking, and financial industries. Professor April has been developing healthcare HPC applications in the area of genomic visualization, genotyping sequencing, and whole genome sequencing, extending Berkeley's Adam data structure for HPC. These applied research projects deploy large-scale machine learning algorithms in research hospitals for specific use cases, such as type 2 diabetes early prediction and leukemia treatments in children.

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